Next Generation Data warehouses
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Next Generation
Data Warehouses
www.yash.com
About the Presenter
• Gautam Gupta – Practice Manager, BI
and Data Warehousing at YASH
Technologies
• Over 20 years of experience in the IT
industry, including extensive consulting
experience in US and Europe.
• Currently heads the BI and Data
Warehousing competency at YASH
since 2005, and has successfully
delivered and managed multiple BI and
Data Warehousing projects across the
world.
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Topics
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DW – What is it
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Data Warehouse Platforms
Note: A data warehouse platform manages a data warehouse, but the two are separate.
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Evolving State of Data
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Evolving State of Data
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Why care about Data Warehouse Platforms ?
Business face changes rapidly
Support changing business requirements
DW mature through multiple lifecycle stages
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Buzz About Big Data
• Global Internet population grew by 7% from
2011 to 2012 and now represents about 3 billion
people approx.
• Every Minute
– 571 new websites
– 217 New Users
– 48 Hours of You Tube footage uploaded
– Two million Google search queries
– 648 478 Facebook users sharing content
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Challenges in current Data Warehouse
Platforms
• Support for Advanced Analytics
• Real-time or On-demand workloads
• Support for Large Data Volume
• Support of Large number of Concurrent Users
• Scaling Cost
• Inadequate support for web-services and SOA
• Inadequate support for in-memory processing
• SMP Vs MPP
• Speed
• Support for Mashed Data
• Availability
• 64 Bit
• Data Vertulization
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New Analytics Needs
• Acquisition of environment data
• Correlation of subjective data
• Visualization of complex data
• Analysis of Event Stream data
• Need for pattern discovery
• Need for predictive modeling and scoring
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Demands on New Architecture
• Fast Analytics
• Flexible ad-hoc transformations
• Storage of granular AND semi-transformed data
• Storage of temporal data
• Interpretation of subjective data
• Ability to add new data for new analysis with no disruption
• Cost-effective scaling
• Statistical analysis / Predictive modeling
• Automated meta-data extraction / learning
• Ability to analyze real-time event-streams
• Provide existing operational reporting, online ad-hoc queries, “state-of-the-business”
dashboards
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Candidate Architecture
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Candidate Architecture
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Candidate Architecture
* Intelligent Business Strategies
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Big Data Portfolio
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Candidate Arch. - DWA
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Cloud Computing and Software-as-a-Service (Saas)
Here?
3-5 yrs?
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Workloads ready now for cloud computing: TOP 25
Analytics • Data mining, text mining or
other analytics • Data warehouses or data
marts • Transactional databases
Business services • Customer relationship
management (CRM) or sales force automation
• E-mail • Enterprise resource planning
(ERP) applications • Industry-specific applications
Collaboration • Audio/video/Web
conferencing • Unified communications • VoIP infrastructure
Desktop and devices Desktop Service/help desk
Development and test Development environment Test environment
Infrastructure Application servers Application streaming Business continuity/
disaster recovery Data archiving Data backup Data center network capacity Security Servers Storage Training infrastructure Wide area network (WAN)
capacity
Source: IBM Market Insights, Cloud Computing Research, July 2012.
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Workloads may be at different levels of readiness for cloud
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There is a spectrum of deployment options for
cloud computing
Private Public
Hybrid
IT capabilities are provided “as a
service,” over an intranet, within the
enterprise and behind the firewall
Internal and external service delivery
methods are integrated
IT activities / functions are
provided “as a service,” over
the Internet
Third-party
operated
Third-party hosted
and operated
Enterprise data center
Enterprise data center
Private cloud Hosted private cloud
Managed private cloud
Enterprise
Shared cloud services
A
Enterprise
B
Public cloud services
A
Users
B
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How Can We Bridge the Cloud & On Premise Worlds?
Home-grown
Applications
Packaged
Applications
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Summary: Key Benefits of Cloud
• Cloud enables the dynamic availability of IT
applications and infrastructure, regardless of
location.
– Enhanced service delivery reinforces efforts for
customer retention, faster time to market and
horizontal market expansion.
• Cloud computing promotes IT optimisation so
that IT resources are configured for maximum
cost-benefit.
– It supports massive scalability to meet periods of
demand while avoiding extended periods of under-
utilised IT capacity
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Recommendations
• Plan for the next generation data warehouse that is in your near future
• Recognize that next generation technology drivers are really business drivers
• Avoid assembling your own data warehouse platform
• Plan for big data
• Be open to low-cost DW platform options
• Don’t forget options outside the DW platform
• Expect analytics to be a priority for your next generation DW platform
• Note that some next generation options are a critical path to others
• Realize that your next generation DW platform may require multiple platforms
• Be open to alternative DBMSs
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Thank You!
mailto: [email protected]
website : www.yash.com
© YASH Technologies, 1996-2008. All rights reserved.
The information in this document is based on certain assumptions and as such is subject to change. No part of
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makes reference to trademarks that may be owned by others. The use of such trademarks herein is not as
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